A Model of Event Knowledge

We present a connectionist model of event knowledge that is trained on examples of sequences of activities that are not explicitly labeled as events. The model learns co-occurrence patterns among the components of activities as they occur in the moment (entities, actions, and contexts), and also learns to predict sequential patterns of activities. In so doing, the model displays behaviors that in humans have been characterized as exemplifying inferencing of unmentioned event components, the prediction of upcoming components (which may or may not ever happen or be mentioned), reconstructive memory, and the ability to flexibly accommodate novel variations from previously encountered experiences. All of these behaviors emerge from what the model learns

Semantic and Associative Relations in Adolescents and Young Adults: Examining a Tenuous Dichotomy

The constructs of semantic and associative relatedness have played a prominent role in research on semantic memory because researchers have historically drawn on the distinction between these two types of relations when formulating theories, creating experimental conditions, and explaining empirical results. We argue that the binary distinction between semantics and association is rooted in a fundamental problem in how the two are defined and contrasted. Whereas semantic relatedness has typically been limited to category coordinates, associative relatedness has most often been operationalized using the word association task. We show that meaningful semantic relations between words/concepts certainly extend beyond category coordinates, that word association is driven primarily by meaningful semantic relations between cue and response words, and that non-meaningful, purely associative relations between words generally are not retained in memory. To illustrate these points, we discuss research on semantic priming, picture naming, and the Deese-Roediger-McDermott false memory paradigm. Furthermore, we describe how research on the development of mnemonic skills in adolescents supports our view. That is, adolescents do not learn arbitrary associations between words, but develop elaborative strategies for linking words by drawing on their rich knowledge of events and situations. In other words, adolescents use existing memories of meaningful relations to ground their memories for novel word pairs, even in an associative learning paradigm

Shared Features Dominate Semantic Richness Effects for Concrete Concepts

When asked to list semantic features for concrete concepts, participants list many features for some concepts and few for others. Concepts with many semantic features are processed faster in lexical and semantic decision tasks [Pexman, P. M., Lupker, S. J., & Hino, Y. (2002). The impact of feedback semantics in visual word recognition: Number-of-features effects in lexical decision and naming tasks. Psychonomic Bulletin & Review,9, 542–549; Pexman, P. M., Holyk, G. G., & MonFils, M.-H. (2003). Number-of-features effects and semantic processing. Memory & Cognition,31,842–855]. Using both lexical and concreteness decision tasks, we provided further insight into these number-of-features (NoF) effects. We began by replicating the effect using a larger and better controlled set of items. We then investigated the relationship between NoF and feature distinctiveness and found that features shared by numerous concrete concepts such as facilitate decisions to a greater extent than do distinctive features such as . Finally, we showed that NoF effects are carried by shared visual form and surface, encyclopedic, tactile, and taste knowledge. We propose a decision-making account of these results, rather than one based on the computation of word meaning

False Recall in the Deese–Roediger–Mcdermott Paradigm: The Roles of Gist and Associative Strength

Theories of false memories, particularly in the Deese–Roediger–McDermott (DRM) paradigm, focus on word association strength and gist. Backward associative strength (BAS) is a strong predictor of false recall in this paradigm. However, other than being defined as a measure of association between studied list words and falsely recalled nonpresented critical words, there is little understanding of this variable. In Experiment 1, we used a knowledge-type taxonomy to classify the semantic relations in DRM stimuli. These knowledge types predicted false-recall probability, as well as BAS itself, with the most important being situation features, synonyms, and taxonomic relations. In three subsequent experiments, we demonstrated that lists composed solely of situation features can elicit a gist and produce false memories, particularly when monitoring processes are made more difficult. Our results identify the semantic factors that underlie BAS and suggest how considering semantic relations leads to a better understanding of gist formation

Prediction-Based Learning and Processing of Event Knowledge.

Knowledge of common events is central to many aspects of cognition. Intuitively, it seems as though events are linear chains of the activities of which they are comprised. In line with this intuition, a number of theories of the temporal structure of event knowledge have posited mental representations (data structures) consisting of linear chains of activities. Competing theories focus on the hierarchical nature of event knowledge, with representations comprising ordered scenes, and chains of activities within those scenes. We present evidence that the temporal structure of events typically is not well-defined, but it is much richer and more variable both within and across events than has usually been assumed. We also present evidence that prediction-based neural network models can learn these rich and variable event structures and produce behaviors that reflect human performance. We conclude that knowledge of the temporal structure of events in the human mind emerges as a consequence of prediction-based learning

Conceptual Hierarchies in a Flat Attractor Network: Dynamics of Learning and Computations

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory

Multimodal Event Knowledge in Online Sentence Comprehension: The Influence of Visual Context on Anticipatory Eye Movements

People predict incoming words during online sentence comprehension based on their knowledge of real-world events that is cued by preceding linguistic contexts. We used the visual world paradigm to investigate how event knowledge activated by an agent-verb pair is integrated with perceptual information about the referent that fits the patient role. During the verb time window participants looked significantly more at the referents that are expected given the agent-verb pair. Results are consistent with the assumption that event-based knowledge involves perceptual properties of typical participants. The knowledge activated by the agent is compositionally integrated with knowledge cued by the verb to drive anticipatory eye movements during sentence comprehension based on the expectations associated not only with the incoming word, but also with the visual features of its referent

The Wind Chilled the Spectators, but the Wine Just Chilled: Sense, Structure, and Sentence Comprehension

Anticipation plays a role in language comprehension. In this article, we explore the extent to which verb sense influences expectations about upcoming structure. We focus on change of state verbs like shatter, which have different senses that are expressed in either transitive or intransitive structures, depending on the sense that is used. In two experiments we influence the interpretation of verb sense by manipulating the thematic fit of the grammatical subject as cause or affected entity for the verb, and test whether readers’ expectations for a transitive or intransitive structure change as a result. This sense-biasing context influenced reading times in the postverbal regions. Reading times for transitive sentences were faster following good-cause than good-theme subjects, but the opposite pattern was found for intransitive sentences. We conclude that readers use sense-contingent subcategorization preferences during on-line comprehension